Welcome to LDBC Website

On this website, you can find information on benchmark specifications and results, on how the LDBC organization works, the motivation for LDBC, and benchmarking resources for the graph and RDF developer community.

PUBLIC

LDBC brings industry and users together for developing benchmarks whereby the state-of-the-art and advances in graph database technologies can be assessed and directed. Read More to find out how the LDBC might help you.

BENCHMARKS

Here you may find the results for different benchmarks, i.e. the Social Network Benchmark (SNB) and the Semantic Publishing Benchmark (SPB), their definitions and best practices, the repositories where to find the data generators and the query implementations, an access to the intranet for the LDBC industry partners and a list of the LDBC member vendors.

Next 31st of May the GRADES workshop will take place in Melbourne within the ACM/SIGMOD presentation. GRADES started as an initiative of the Linked Data Benchmark Council in the SIGMOD/PODS 2013 held in New York. Read more information about the event here.

​SNB Interactive is the wild frontier, with very few rules. This is necessary, among other reasons, because there is no standard property graph data model, and because the contestants support a broad mix of programming models, ranging from in-process APIs to declarative query.

LDBC is presenting two papers at the next edition of the ACM SIGMOD/PODS conference held in Melbourne from May 31st to June 4th, 2015. The annual SCM SIGMOD/PODS conference is a leading international forum for database researchers, practitioners, developers, and users to explore cutting-edge ideas and results, and to exchange techniques, tools and experiences.

During last TUC Meeting in Barcelona we were glad to welcome Mark D. Wilkinson from Universidad Politécnica de Madrid with his presentation "SADI: A design-pattern for “native” Linked-Data Semantic Web Services".

Check the slides and video to learn more about how SADI uses OWL and RDF and about SHARE the health research environment that answers SPARQL queries with SADI.

This post is the first in a series of blogs analyzing the LDBC Social Network Benchmark Interactive workload. This is written from the dual perspective of participating in the benchmark design and of building the OpenLink Virtuoso implementation of same.

The second part of presentations during the first day at the TUC Meeting in Barcelona started with the presentation from JervenBolleman from the Swiss Institute of Bioinformatics called "20 billion triples in production".

Watch Jerven Bolleman talking about why and how the Uniprot SPARQL endpoint allows working with billion of triples from biological datasets.

The second presentation during last LDBC's 6th TUC Meeting that took place in Barcelona was called SPIMBENCH: A Scalable, Schema-Aware, Instance Matching Benchmark for the Semantic Publishing Domain and presented by Tzanina Saveta from FORTH.

In a previous 3-part blog series we touched upon the difficulties of executing the LDBC SNB Interactive (SNB) workload, while achieving good performance and scalability. What we didn't discuss is why these difficulties were unique to SNB, and what aspects of the way we perform workload execution are scientific contributions - novel solutions to previously unsolved problems. This post will highlight the differences between SNB and more traditional database benchmark workloads. Additionally, it will motivate why we chose to develop a new wo